Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model Gen Li Tsinghua Y uting Wei CMU Y uejie Chi CMU Y uantao Gu Tsinghua Y uxin Chen Princeton

Neural Information Processing Systems 

Despite a number of prior work tackling this problem, a complete picture of the trade-offs between sample complexity and statistical accuracy is yet to be determined.

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